For Places365-LT, we used ResNet-{50,152} with a batch size of 256 and 128 respectively on four 1080Ti GPUs.
The models are pretrained on the full ImageNet dataset, following [1]}. We trained the models for 30 epochs with multi-step learning rate scheduler, which decays by 0.1 at epoch 10, 20 respectively. The learning rate is initialized as 0.1 for the classifier and 0.01 for the backbone.
